{"id":"https://openalex.org/W4317419032","doi":"https://doi.org/10.1109/vtc2022-fall57202.2022.10012698","title":"Deep Reinforcement Learning Based Resource Allocation for LoRaWAN","display_name":"Deep Reinforcement Learning Based Resource Allocation for LoRaWAN","publication_year":2022,"publication_date":"2022-09-01","ids":{"openalex":"https://openalex.org/W4317419032","doi":"https://doi.org/10.1109/vtc2022-fall57202.2022.10012698"},"language":"en","primary_location":{"id":"doi:10.1109/vtc2022-fall57202.2022.10012698","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2022-fall57202.2022.10012698","pdf_url":null,"source":{"id":"https://openalex.org/S4363607792","display_name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058717745","display_name":"Aohan Li","orcid":"https://orcid.org/0000-0003-0618-4894"},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Aohan Li","raw_affiliation_strings":["The University of Electro-Communications,Graduate School of Informatics and Engineering,Tokyo,Japan","Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Electro-Communications,Graduate School of Informatics and Engineering,Tokyo,Japan","institution_ids":["https://openalex.org/I20529979"]},{"raw_affiliation_string":"Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo, Japan","institution_ids":["https://openalex.org/I20529979"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5058717745"],"corresponding_institution_ids":["https://openalex.org/I20529979"],"apc_list":null,"apc_paid":null,"fwci":2.2556,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.90122731,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12079","display_name":"IoT Networks and Protocols","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12079","display_name":"IoT Networks and Protocols","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11392","display_name":"Energy Harvesting in Wireless Networks","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9829000234603882,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.83370441198349},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.6292661428451538},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6192225813865662},{"id":"https://openalex.org/keywords/default-gateway","display_name":"Default gateway","score":0.6136318445205688},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.5656668543815613},{"id":"https://openalex.org/keywords/transmission","display_name":"Transmission (telecommunications)","score":0.5459105968475342},{"id":"https://openalex.org/keywords/channel-state-information","display_name":"Channel state information","score":0.5314751267433167},{"id":"https://openalex.org/keywords/train","display_name":"Train","score":0.5073298811912537},{"id":"https://openalex.org/keywords/synchronization","display_name":"Synchronization (alternating current)","score":0.5031232237815857},{"id":"https://openalex.org/keywords/resource-allocation","display_name":"Resource allocation","score":0.464796245098114},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4512287378311157},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.4471408426761627},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.36848270893096924},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.36159810423851013},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3071523904800415},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.25308936834335327},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.2395181655883789},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09346523880958557}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.83370441198349},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.6292661428451538},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6192225813865662},{"id":"https://openalex.org/C187713609","wikidata":"https://www.wikidata.org/wiki/Q2465461","display_name":"Default gateway","level":2,"score":0.6136318445205688},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.5656668543815613},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.5459105968475342},{"id":"https://openalex.org/C148063708","wikidata":"https://www.wikidata.org/wiki/Q5072511","display_name":"Channel state information","level":3,"score":0.5314751267433167},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.5073298811912537},{"id":"https://openalex.org/C2778562939","wikidata":"https://www.wikidata.org/wiki/Q1298791","display_name":"Synchronization (alternating current)","level":3,"score":0.5031232237815857},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.464796245098114},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4512287378311157},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.4471408426761627},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.36848270893096924},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.36159810423851013},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3071523904800415},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.25308936834335327},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.2395181655883789},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09346523880958557},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vtc2022-fall57202.2022.10012698","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2022-fall57202.2022.10012698","pdf_url":null,"source":{"id":"https://openalex.org/S4363607792","display_name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8600000143051147}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2098046554","https://openalex.org/W2613332842","https://openalex.org/W2896592586","https://openalex.org/W3081345078","https://openalex.org/W3105509069","https://openalex.org/W3112255959","https://openalex.org/W3133776659","https://openalex.org/W3158390398","https://openalex.org/W3198237197","https://openalex.org/W3198473580","https://openalex.org/W3212556128","https://openalex.org/W4205630984","https://openalex.org/W4210754515","https://openalex.org/W4213425359","https://openalex.org/W4285161461","https://openalex.org/W4298411960","https://openalex.org/W6843495587"],"related_works":["https://openalex.org/W618248309","https://openalex.org/W2377336366","https://openalex.org/W1568097102","https://openalex.org/W4390419160","https://openalex.org/W1601203902","https://openalex.org/W2075798043","https://openalex.org/W2102464536","https://openalex.org/W4225671779","https://openalex.org/W2361332776","https://openalex.org/W2248934910"],"abstract_inverted_index":{"It":[0],"is":[1,100,128],"predicted":[2],"that":[3,251],"the":[4,39,44,55,122,137,141,146,177,181,189,198,224,242,252,257],"number":[5,201,217],"of":[6,8,24,125,140,202,245],"Internet":[7],"Things":[9],"(IoT)":[10],"devices":[11,26,56,95,127],"will":[12,27],"be":[13,28,151],"more":[14],"than":[15],"75":[16],"billion":[17],"by":[18,32],"2025,":[19],"where":[20],"a":[21,71,164],"large":[22],"portion":[23],"IoT":[25,94,246],"long-range":[29],"(LoRa)":[30],"powered":[31],"batteries.":[33],"The":[34,60],"battery":[35],"lifetime":[36],"limitations":[37],"and":[38,109,197,218,228],"spectrum":[40,62,81],"shortage":[41],"have":[42],"been":[43],"main":[45],"problems":[46],"in":[47,57,79,104,131,155,235,263],"realizing":[48],"LoRa":[49,126,142,204,208],"wide":[50],"area":[51],"network":[52,184],"(LoRAWAN)":[53],"for":[54,171],"hard-toreach":[58],"areas.":[59],"dynamic":[61],"access":[63],"technique":[64],"has":[65],"gained":[66],"tremendous":[67],"research":[68],"interest":[69],"as":[70,114],"promising":[72],"paradigm":[73],"due":[74],"to":[75,84,90,153],"its":[76,215],"outstanding":[77],"performance":[78],"improving":[80],"efficiency.":[82],"How":[83],"realize":[85],"intelligent":[86],"resource":[87],"allocation":[88],"(RA)":[89],"avoid":[91],"collisions":[92],"among":[93],"with":[96],"low":[97],"energy":[98,123,138,243],"consumption":[99,124],"an":[101],"important":[102],"problem":[103],"LoRaWAN.":[105,172],"However,":[106],"either":[107],"synchronization":[108],"prior":[110,148,229],"information":[111,117,149,222,230],"estimation,":[112],"such":[113],"channel":[115],"state":[116],"(CSI),":[118],"are":[119,232],"required,":[120],"or":[121,195,220],"not":[129,233],"considered":[130],"related":[132],"work,":[133],"which":[134,239],"may":[135,150,240],"decrease":[136],"efficiency":[139,244],"devices.":[143,247],"In":[144,173],"addition,":[145],"necessary":[147],"challenging":[152],"obtain":[154],"future":[156],"networks.":[157],"To":[158],"address":[159],"these":[160],"issues,":[161],"we":[162],"propose":[163],"deep":[165,182],"Q":[166],"learning-based":[167],"RA":[168],"(DQLRA)":[169],"method":[170,254],"our":[174,236],"proposed":[175,237,253],"method,":[176,238],"gateway":[178],"(GW)":[179],"trains":[180],"neural":[183],"(DNN)":[185],"only":[186],"based":[187,213],"on":[188,214],"transmission":[190,193],"state,":[191],"i.e.,":[192],"failure":[194],"success,":[196],"corresponding":[199],"device":[200,209,216],"each":[203,207],"device.":[205],"Then,":[206],"can":[210,255],"make":[211],"decisions":[212],"ACK":[219],"NACK":[221],"using":[223],"trained":[225],"DNN.":[226],"Synchronization":[227],"estimation":[231],"required":[234],"improve":[241],"Simulation":[248],"results":[249],"show":[250],"achieve":[256],"optimal":[258],"frame":[259],"success":[260],"rate":[261],"(FSR)":[262],"most":[264],"scenarios.":[265]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-05T09:29:38.588285","created_date":"2025-10-10T00:00:00"}